Szczegóły publikacji
Opis bibliograficzny
Generic sensor model for object detection algorithms validation / Kamil LELOWICZ, Michał JASIŃSKI, Marcin Piątek // W: Advanced, contemporary control : proceedings of KKA 2020 – the 20th Polish control conference : [14-16 October, 2020], Łódź, Poland / eds. Andrzej Bartoszewicz, Jacek Kabziński, Janusz Kacprzyk. — Cham : Springer Nature Switzerland AG, cop. 2020. — (Advances in Intelligent Systems and Computing ; ISSN 2194-5357 ; vol. 1196). — ISBN: 978-3-030-50935-4; e-ISBN: 978-3-030-50936-1. — S. 1249–1260. — Bibliogr. s. 1259-1260, Abstr. — Publikacja dostępna online od: 2020-06-24. — K. Lelowicz, M. Jasiński - dod. afiliacja: APTIV Services Poland S.A.
Autorzy (3)
- AGHLelowicz Kamil
- AGHJasiński Michał
- Piątek Marcin
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 129304 |
|---|---|
| Data dodania do BaDAP | 2020-07-16 |
| DOI | 10.1007/978-3-030-50936-1_104 |
| Rok publikacji | 2020 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Czasopismo/seria | Advances in Intelligent Systems and Computing |
Abstract
In the artificial intelligence era of perception algorithms being used in the state-of-the-art Advance Driver Assistance Systems, algorithm validation is not an easy task, mainly due to the amount of sensor data that must be processed at once. To provide the highest possible safety level of the solution, algorithm performance must be assessed in various difficult conditions. To address this problem, a novel Generic Sensor Model algorithm is presented, which can be directly incorporated in performance analysis of the perception algorithm in highly occluded driving scenarios. In this paper, the Generic Sensor Model algorithm is comprehensively described and its usefulness and robustness are proven with a set of experiments.
